Review Reports

Round 1

Reviewer 1 Report

-Specify the conditions of Table 3.

-Equation 3 is badly written.

-Specify how you evaluate the IPF, Cp

Author Response

Response to Reviewer 1 Comments

Point 1:  Specify the conditions of Table 3.

Response 1: Thanks for your valuable comments. In the experiment, 4 wt% sodium chloride aqueous solution was used as the base liquid, and different concentrations of silica nanofluid were prepared. Table 5 (corresponding to the Table 3 in the original manuscript) shows the specific heat of silica nanofluid at different concentrations of 0.05 wt%, 0.1 wt%, 0.2 wt%, 0.5 wt%, 0.75 wt%, and 1 wt%. The calculation conditions of the specific heat of silica nanofluids are the specific heat of 4 wt% aqueous sodium chloride solution and the specific heat of nanosilica (1000 J/kg K). The specific heat of the nanofluid is evaluated according to the formula 3, which has been found appropriate for use with nanofluids as validated by O’Hanley et al and Ferrouillat et al. The corresponding revisions are highlighted by red color. (page 7, line 206-210 )

Point 2: Equation 3 is badly written.

Response 2: Thanks for your helpful comments. Equation 3 is rewritten according to reference [1] and the format requirements of the journal. The corresponding revisions are highlighted by red color. (page 7, line 201-203)

Point 3: Specify how you evaluate the IPF, Cp

Response 3: Thanks for your valuable comments.

The evaluation of IPF was based on calorimetry method and the energy conservation principle. It was assumed that there was negligible heat loss during the measurement process. The value of IPF was calculated by measuring the initial and final temperatures and masses of the sample after mixing with 200 g of hot water at 40°C. In order to reduce the experimental error and improve the accuracy of the experimental data, the IPF of each ice slurry sample for different ice-making time was measured three times and the average value was used for analysis.

In order to verify the reliability of this meathod for IPF measurement, the solid crushed ice with the masses of 10, 20, 30, 40 and 50 g was weighed and added to 150 g of liquid water at 0°C The ice slurries with theoretical IPF of 6.25%, 11.76%, 16.67%, 21.05% and 25.0% were obtained, and then the IPF of each ice slurry sample was measured according to the calorimetry method. The calculated results were 6.12%, 11.64%, 16.83%, 21.19% and 24.73%, respectively. Comparing the above data, it can be seen that the error between the experimental value and the theoretical value is small. Therefore, it is considered that the IPF obtained by the calorimetry method is reliable.

In the revised manuscript, we describe the evaluation method of IPF in more detail. The corresponding revisions are highlighted by red color. (page 5, line 160-166 )

The specific heat of aqueous sodium chloride solution varies with the mass concentration of sodium chloride and the temperature of the solution. During the process of the measurement of IPF, the average temperature before and after the ice slurry melts is approximately 273.1 K, so the specific heat at 273.1 K is used as the condition for the evaluation of the specific heat of aqueous sodium chloride solution.

The specific heat of the nanofluid is evaluated according to the formula 3. In the experiment, 4 wt% sodium chloride aqueous solution was used as the base liquid, and different concentrations of silica nanofluid were prepared. The calculation conditions of the specific heat of silica nanofluids are the specific heat of 4 wt% aqueous sodium chloride solution and the specific heat of nanosilica, which equals to 1000 J/kg K. 

The corresponding revisions are highlighted by red color. (page 7, line195-199, 206-210)

Reference

1. O’Hanley H.; Buongiorno J.; McKrell T.; Hu L.W. Measurement and model validation of specific heat capacity with differential scanning calorimetry. Adv. Mech. Eng. 2012, Article ID 181079, 6 pp. https://doi.org/10.1155/2012/181079

Reviewer 2 Report

This study is interesting and relevant for the journal but requires some amendments and clarifications. The main concerns of the reviewer are the followings:

In introduction, define what the author mean by "supercooling degree".

In section 2.3:

Give reference of nanofluids used with link to website of manufacturer. Type of base fluid is not mentioned. Include all manufacturer data. line 155 an average value of 25nm is given, demonstrated by TEM picture, a value of 2 nm is given in Table1.

What is the concentration in nanoparticles in fig3?

The use of eq 3 requires to know Cp of silica and sodium chloride, so provide these values.

Line 282: this point is unclear, clearly explain the process of dilution (or in material section) and calculation of concentration as water, some unknown additives, silica nanoparticles and sodium chlorure are present.

Results of figure 15 are poorly explain. Authors must remove Fig.17 as they don't state about the change in nanoparticle size before, and results are not convincing.

Author Response

Response to Reviewer 2 Comments

 

Point 1:  In introduction, define what the author mean by "supercooling degree".

Response 1: Thanks for your helpful comments. In the previous literatures [1], the supercooling degree is defined as (T-T_f) K, where T is the tempearature of the theoretical freezing point and T_f is the temperature immediately before supercooling dissolution. In this paper, we have followed this definition. The corresponding revisions are highlighted by red color. (page 2, line 75-77)

 

Point 2: In section 2.3: Give reference of nanofluids used with link to website of manufacturer. Type of base fluid is not mentioned. Include all manufacturer data. line 155 an average value of 25nm is given, demonstrated by TEM picture, a value of 2 nm is given in Table1.

Response 2: Thanks for your helpful comments.

The silica nanofluid with average particle diameter of 25 nm used in the experiments was supplied directly by Shenzhen Jingcai Co., Ltd (Shenzhen, China) at an original concentration of 30 wt% (http://www.nanolly.com). The base fluid of the silica nanofluid provided by the manufacturer is deionized. We were unable to determine the different surfactants or dispersants the manufacturer employed as additives to stabilize the nanofluids, because this is proprietary information.

The nanofluids with different silica concentration were examined for particle size distribution under TEM and Figure 3 was just an example of TEM image. In the initial manuscript, the effects of nanosilica with different particle sizes on system performance at the same additive concentration (0.5 wt%) were compared, as shown in Figure 17. According to your valuable comment (Point 6), we remove Figure 17 and the related description in the revised manuscript. Therefore, in the revised manuscript, we only consider the uncertainty of nanosilica size in nanofluids with a given average particle size of 25 nm. From all the TEM images, we found that the measured particle size was between 24.5 and 25.3 nm, thus the actual uncertainty is 0.5 nm. The corresponding revisions are highlighted by red color. (page 5, line 137; page 6, line 168-173)

 

Point 3: What is the concentration in nanoparticles in fig3?

Response 3: Thanks for your valuable comments. The concentration of nanosilica in Fig. 3 is 0.5%. The corresponding revisions are highlighted by red color. (page 6, line 179)

 

Point 4: The use of eq3 requires to know Cp of silica and sodium chloride, so provide these values.

Response 4: Thanks for your valuable comments. In the experiment, 4 wt% sodium chloride aqueous solution was used as the base liquid, and different concentrations of silica nanofluid were prepared. Therefore, the specific heat of sodium chloride solution in Eq. 3 refers to the specific heat of 4 wt% aqueous sodium chloride solution, and its value is shown in Table 4. The specific heat of nanosilica equals to 1000 J/kg K, which is obtained by querying the handbook of physical property parameter. The corresponding revisions are highlighted by red color. (page 7, line 206-210)

 

Point 5: Line 282: this point is unclear, clearly explain the process of dilution (or in material section) and calculation of concentration as water, some unknown additives, silica nanoparticles and sodium chlorure are present.

Response 5: Thanks for your valuable comments. The silica nanofluids used in the experiments were supplied directly by the manufacturer at an original concentration of 30%. We were unable to determine the different surfactants or dispersants the manufacturer employed as additives to stabilize the nanofluids, because this is proprietary information. During the experiment, a certain amount of deionized water and sodium chloride were added to dilute the mother nanofluids to obtain the desired concentration of the silica nanofluids. Each time 1 kg of nanofluid was prepared and the composition is shown in Table 3. The corresponding revisions are highlighted by red color. (page 6, line 173-175, 188)

Table 3. The composition of different concentrations of silica nanofluids

Mass concentrations (%)	Deionized water (g)	Sodium chloride (g)	Parent nanofluid (g)
0.05	958.33	40	1.67
0.1	956.67	40	3.33
0.2	953.33	40	6.67
0.5	943.33	40	16.67
0.75	935	40	25.0
1	926.67	40	33.33

 

Point 6: Results of figure 15 are poorly explain. Authors must remove Fig.17 as they don't state about the change in nanoparticle size before, and results are not convincing.

Response 6: Thanks for your valuable comments. In the revised manuscript, we have removed Fig. 17 and explained Fig. 15 in more detail. As shown in Fig. 15, as the concentration of nanosilica increased, the time required for the formation of ice slurry decreased from 1030 seconds to 840 seconds. Based on the heterogeneous nucleation theory [2], if there are solid particles in parent phase, crystal nucleus will be formed firstly on the solid particle surface, which contributes to reducing nucleation work. As we know, heterogeneous nucleation is the main form of nucleation, and the use of nanosilica as a nucleating agent induced heterogeneous nucleation and advance the freezing time. However, the formation temperature of ice slurry fluctuated between -2.3 and -2.4°C under different nanosilica concentrations, which indicates that nanosilica has little effect on increasing the freezing point temperature.Combined with the opinions of other reviewers, we have revised the manuscript, and the corresponding revisions are highlighted by red color. (page 13, line 320-328)

 

Reference

1.         Koji M.; Yoshito I.; Daisauke S.; Keisuke H. Investigation of the influence of surfactant on the degree of supercooling (coexisting system of solid-liquid and gas-liquid interfaces). Int. J. Refrig. 2013, 36, 1302-1309. https://doi.org/10.1016/j.ijrefrig.2013.02.007

2.         Knopf D.A.; Koop T. Heterogeneous nucleation of ice on surrogates of mineral dust. J. Geophys. Res. 2006, 111, 2193–2214. https://doi.org/10.1029/2005JD006894

 

 

Author Response File: Author Response.docx

Reviewer 3 Report

The paper entitled Performance study and efficiency improvement of ice slurry production by scraped-surface method written by Liu et al. is about the experimental investigation of  the performance of ice slurry production by scraped-surface method. Temperature change characteristics,IPF of ice slurry, power consumption of scraping system and COP. They showed increase in the concentration caused a decrease in the IPF and a decrease in the COP. The major points are :

1- Add recent researches and applications in literature

DOI: 10.14716/ijtech.v8i7.686

Polymer, Volume 127, 3 October 2017, Pages 141-149

Applied Thermal Engineering, Volume 51, Issues 1–2, March 2013, Pages 1255-1262

International Journal of Refrigeration, Volume 33, Issue 8, December 2010, Pages 1491-1505

Chinese Journal of Chemical Engineering, Volume 16, Issue 4, 2008, Pages 552-557

2- As presented in Fig 10 the IPF is not an important parameter in ice-making. Why the author insist on keeping that parameter and didn't consider other cases.

3- Figure 16 should  be re-scaled . The current zoom around 2 is fallacious.

4- what is the reason of rapid changes in generation time at figure 9?

5- The detail of scraping system should be presented in a table.

6- Error analysis of experiments is needed.

Author Response

Response to Reviewer 3 Comments

Point 1: Add recent researches and applications in literature

DOI: 10.14716/ijtech.v8i7.686

Polymer, Volume 127, 3 October 2017, Pages 141-149

Applied Thermal Engineering, Volume 51, Issues 1–2, March 2013, Pages 1255-1262

International Journal of Refrigeration, Volume 33, Issue 8, December 2010, Pages 1491-1505

Chinese Journal of Chemical Engineering, Volume 16, Issue 4, 2008, Pages 552-557 

Response 1: Thanks for your helpful comments. We have added these valuable literatures in the revised manuscript (References 7, 25, 38, 4, 11).

Point 2: As presented in Fig 10 the IPF is not an important parameter in ice-making. Why the author insist on keeping that parameter and didn't consider other cases.

Response 2: Thanks for your helpful comments. In this study, the main performance parameters of ice slurry production, including ice slurry formation temperature, ice slurry generation time, IPF, COP of the system were measured. The IPF of ice slurry under different experimental conditions reflects the rate of ice slurry production and it is a parameter necessary for the calculation of COP. Therefore, this parameter is continuously observed in this paper.

Point 3: Figure 16 should be re-scaled. The current zoom around 2 is fallacious.

Response 3: Thanks for your valuable comments. We have re-scaled the Fig. 16. The corresponding revisions are highlighted by red color. (page 14, line 341-342)

Point 4: What is the reason of rapid changes in generation time at figure 9?

Response 4: Thanks for your valuable comments. The flow rates of 1.0, 1.1, 1.2, 1.3, 1.4, and 1.5 m3/h corresponded to the ice slurry generation time of 1180, 1140, 1110, 1080, 1160, 1180 seconds, respectively. When the flow rate was increased from 1.3 to 1.4 m3/h, the ice slurry generation time was extended from 1080 seconds to 1160 seconds, an increase of 7.41%. During the experiment, we observed that when the flow rate increased to 1.4 m3/h, the ice-making solution flowed out of the annular shower tube with a serious splash and part of the solution did not flow down the inner wall surface. Therefore, the solution actually participating in the effective heat exchange through the inner wall surface was reduced and the amount of cold obtained per unit time of the ice-making solution was also decreased, resulting in the increase of ice slurry generation time and the decrease of the system COP. The corresponding revisions are highlighted by red color. (page 10-11, line 280-288)

Point 5: The detail of scraping system should be presented in a table.

Response 5: Thanks for your valuable comments. The detail of scraping system is presented in Table 1 in the revised manuscript. The corresponding revisions are highlighted by red color. (page 4, line 136)

Point 6: Error analysis of experiments is needed.

Response 6: Thanks for your valuable comments. In this paper, the reliability of the measurement results is represented through the uncertainty analysis. The uncertainties of direct measurement parameters given by the manufacturers are listed in Table 2, including temperature, volume flow rate, power consumption and weight. The sources of measurement errors are analyzed and the uncertainties of derivation parameters, such as COP and IPF, are evaluated [1]. The uncertainty of particle size of nanosilica is obtained through the analysis of the TEM images. As shown in Fig. 8, Fig. 11, Fig. 14, Fig. 16, the uncertainty of each experimental value is added to the point. In the figures of the relationship between IPF and ice-making time, since the points in the figures are already very compact, so it is difficult to add the uncertainty on the graph. We summarize the uncertainty of IPF, as shown in Table 2. The corresponding revisions are highlighted by red color. (page 3-4, line 125-131, 137)

Reference

1. Coleman, H.W.; Steele, W.G. Experimentation, Validation, and Uncertainty Analysis for Engineers, 3rd ed.; Wiley: New York, United State, 2009; pp. 29–83.

Author Response File: Author Response.docx

Reviewer 4 Report

This study is about the experimental investigation of ice slurry production using silica nanofluid. This study aims to reveal the effect of silica nanofluid on the ice slurry formation characteristics and the system COP. Despite some useful experimental results, the experimental method and results are not clear for an understanding of readers. Here are some suggestions to improve/revise the manuscript for further process.

 

1. P.3 line 114: Authors need to show the location of PT100 platinum resistance thermometer probe. Are there temperature distributions in the slurry storage tank? The temperature distributions are affected by the COP in Eq.(1).

 

2. P. 12 line 292: There is lack of explanation about induced heterogeneous nucleation using nano-silica. Authors need to describe the mechanisms of decreasing heterogeneous nucleation using nano-silica and promoting thermal conductivity.

Author Response

Response to Reviewer 4 Comments

Point 1:  P.3 line 114: Authors need to show the location of PT100 platinum resistance thermometer probe. Are there temperature distributions in the slurry storage tank? The temperature distributions are affected by the COP in Eq.(1).

Response 1: Thanks for your helpful comments. During the experiment, the solution height of the ice storage tank is about 220 mm. There are three Pt100 thermometer probes within the tank, which are set at a height of 40 mm, 120 mm and 200 mm from the bottom respectively. The tank is equipped with a stirring paddle. During the ice making process, the stirring paddle automatically opened for 30s every 570s, so that the ice slurry solution was evenly mixed. At this time, the real-time temperature was recorded, and it was found that the display temperatures of the three Pt100 thermometer probes were almost the same. Therefore, the measured temperature is the actual temperature of the ice slurry, and does not cause excessive deviation of the COP. The corresponding revisions are highlighted by red color. (page 3, line 116-122)

Point 2: P. 12 line 292: There is lack of explanation about induced heterogeneous nucleation using nano-silica. Authors need to describe the mechanisms of decreasing heterogeneous nucleation using nano-silica and promoting thermal conductivity.

Response 2: Thanks for your helpful comments. Based on the heterogeneous nucleation theory [1], if there are solid particles in parent phase, crystal nucleus will be formed firstly on the solid particle surface, which contributes to reducing nucleation work. As we know, heterogeneous nucleation is the main form of nucleation, and the use of nanosilica as a nucleating agent induced heterogeneous nucleation and advance the freezing time. Meanwhile, existing researches have shown that the addition of nanoparticles to solutions can significantly increase the thermal conductivity of solutions and improve the heat transfer performance [2-8]. Therefore, we speculate that the addition of nanosilica also improves the heat transfer performance of the fluid, thereby achieving a higher COP. However, there is no uniform explanation for the mechanism of the increase in thermal conductivity [9,10].

Combined with the opinions of other reviewers, we have revised the manuscript, and the corresponding revisions are highlighted by red color. (page 13, line 320-328, 333-338)

References

1.   Knopf D.A.; Koop T. Heterogeneous nucleation of ice on surrogates of mineral dust. J. Geophys. Res. 2006, 111, 2193–2214. https://doi.org/10.1029/2005JD006894

2.   Li H.; Wang L.; He Y.; Hu Y.; Zhu J.; Jiang B. Experimental investigation of thermal conductivity and viscosity of ethylene glycol based ZnO nanofluids. Appl. Therm. Eng. 2015, 88, 363–368. https://doi.org/10.1016/j.applthermaleng.2014.10.071

3.   Teng T.P.; Hung Y.H.; Teng T.C.; Mo H.E.; Hsu H.G. The effect of alumina/water nanofluid particle size on thermal conductivity. Appl. Therm. Eng. 2010, 30, 2213–2218. https://doi.org/10.1016/j.applthermaleng.2010.05.036

4.   Sonawane S.; Patankar K.; Fogla A.; Puranik B.; Bhandarkar U.; Kumar S.S. An experimental investigation of thermo-physical properties and heat transfer performance of Al2O3-Aviation Turbine Fuel nanofluids. Appl. Therm. Eng. 2011, 31, 2841–2849. https://doi.org/10.1016/j.applthermaleng.2011.05.009

5.   Khodadadi J.M.; Fan L.; Babaei H. Thermal conductivity enhancement of nanostructure-based colloidal suspensions utilized as phase change materials for thermal energy storage: A review. Renew. Sust. Energ. Rev. 2013, 24, 418–444. https://doi.org/10.1016/j.rser.2013.03.031

6.   Syam S.; Venkata R.; Manoj S.; Antonio S. Thermal conductivity and viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids for heat transfer applications: An experimental study. Int. Commun. Heat Mass 2014, 56, 86-95. https://10.1016/j.icheatmasstransfer.2014.06.009

7.   Fu Y.X.; He Z.X.; Mo D.C.; Lu S.S. Thermal conductivity enhancement of epoxy adhesive using graphene sheets as additives. Int. J. Therm. Sci. 2014, 86, 276-283. https://10.1016/j.ijthermalsci.2014.07.011

8.   Xing M.B. Yu J.L.; Wang R.X. Experimental investigation and modelling on the thermal conductivity of CNTs based nanofluids. Int. J. Therm. Sci. 2016, 104, 404-411. https://10.1016/j.ijthermalsci.2016.01.024

9.   Keblinski P.; Phillpotb S.R.; Choi S.U.S.; Eastmanb J.A. Mechanisms of heat flow in suspensions of nano-sized particles (nanofluids). Int. J. Heat Mass Tran. 2002, 45, 855-863. https://10.1016/S0017-9310(01)00175-2

10.  Yu W.; Choi S.U.S. The role of interfacial layers in the enhanced thermal conductivity of nanofluids: A renovated maxwell model. J. Nanopart. Res. 2003, 5, 167-171. https://10.1007/s11051-004-2601-7

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The reviewer is satisfied with the replies to comments and questions as well as amendments and new data included in the revised version of the paper.

This version can be accepted for publication in Appl. Sciences.

Reviewer 4 Report

Careful discussion for the reviewers' comments has been done.The authors have addressed my concerns.